Handbook of pattern recognition & computer vision
Scale-Space Theory in Computer Vision
Scale-Space Theory in Computer Vision
Surface texture and microstructure extraction from multiple aerial images
Computer Vision and Image Understanding
Computer and Robot Vision
COSIT 2001 Proceedings of the International Conference on Spatial Information Theory: Foundations of Geographic Information Science
Fragmentation in the Vision of Scenes
ICCV '03 Proceedings of the Ninth IEEE International Conference on Computer Vision - Volume 2
A Mathematical Theory of Communication
A Mathematical Theory of Communication
Human Understandable Features for Segmentation of Solid Texture
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
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A new evolutionary approach is presented, based on implicit pattern-process relationships. For implementing this approach, any gray level texture image is decomposed into a progressive sequence of binary patch patterns that describe a process of change from background to foreground domination. Each of the binary patterns throughout these sequences is parameterized, using several metrics that describe, for example, its fragmentation level, both for the background (e.g., white) and foreground (e.g., black) patch patterns. Any texture type is then assumed to have a unique evolutionary path represented by a distinctive region in the feature space of metrics characterizing these patterns and their change. Application of hierarchical clustering based on a few (3 or 4) metrics representing characteristic stages in the patterns' change process allowed us to accurately discriminate between 50 samples of 10 Brodatz texture types.